The problem with short gamma

We have seen markets enter a regime where there appears to be only one direction to price movement. A more accurate way to express this is to say that the return autocorrelation, or price mean aversion [reversion], is high. This was stated in another way in this thread:

Textbooks on options trading will tell you to sell a straddle when you expect the vola to be low. Is this correct? What about in markets that have very little mean reversion and in one direction like we have seen for at least a month? Those sure have low vola. The answer is no, with an explanation detailed below.

The problem is that models like Black-Scholes assumes that autocorrelation is zero (it assumes that markets are efficient, i.e., high AC would mean there are predictable trends), and that you should therefore trade as continuously as your trading costs make reasonable. Well, outside of MMs and high frequency firms, costs usually suck the big one and eat into any premium profit pronto. To add insult to injury, the premium you got was probably too little to finance the replication costs of hedging. [Remember, you as an option trader assume markets are efficient. If you don't believe it why the hell trade options? Just trade the underlying if you believe you can predict trends!]

These two things taken together spell doom for any strategy that is short gamma in this regime for all but the most sophisticated, well capitalized, low cost structured firm/trader. If this structure is not true for you, guess what, you are also delta trading.

What I find interesting is that it seems like volatility can be low, but prices can move strongly over a period of time. Like I mentioned in an earlier thread, GS has moved from 155 range to 175 range so quietly few people noticed and I think IV and HV are real low.

It seems like there should be better way to measure change and not just volatility. For a quick example, if a stock did this in the last 7 trading days:
50
52
54
56
58
60
62
would you want to sell a 65 call for a low price just because the price isn't volatile?
I'm not sure if I'm explaining this correctly, but there is more to price movement then volatility.

Actually, Bernie Schaffer has an example like this in his book. Something like a strong uptrending stock was at $55 and a stock that went up and down quickly and was at $55 and that stock had way more premium, so it was fairly cheap to buy 55 strike calls on the stocks that was a strong uptrender. Interesting to think about anyway.

I just realized something. If it is true that the presence of return autocorrelation affects the volatility and expected value of asset price and BS therefore mis-prices vola [which in turn mis-prices delta/gamma], why not adjust the model such that we make vola functions of time to expiration and correlation coefficient, &#961;? In this new framework the asset price volatility can no longer be expressed as &#963;^2t where &#963;^2 is the variance of asset price returns. Adding &#961; would bias asset price volatility proportional to the autocorrelation coefficient as well as time.

You just need to isolate which greeks are hurting your position and attack those first.

If the market is on a break out, believe it, and then lean deltas in that direction. If you are more contrarian, when you adjust, bring yourself to delta neutral instead of 'bringing the deltas back into control'

Consider some plays to hedge your vega on the downside, back spreads, ratios, long puts, ect.

Might be a good time to hedge with the underlying, especially if you're trading something with a tradable future you can attack the gamma with.

This environment has been difficult for people who like to set up a single short gamma position and then give it slight adjustments through time because the market just slowly grinds and blows right through an expiration loss point. All considered, I would consider some positions with a larger profit zone which may go infinitely in one direction such as a broken wing or imbalanced butterfly, diagonal spread, ratio or ratio write, or perhaps some straddle/strangle combos for risk-margin accounts.

As I have mentioned to you before, nitro, it's all been done already. The whole point of stoch vol models is to treat volatility as a random variable. How to parameterize its behavior is the million dollar question with a whole variety of possible answers. You pick whichever one suits your view.